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DSC
341:
Foundations of Data Science (Formerly CSC 367)

Due to COVID-19, Spring in-class sections will be conducted online. Please contact your instructor for more information.

The course is an introduction to the Data Mining (DM) stages and its methodologies. The course provides students with an overview of the relationship between data warehousing and DM, and also covers the differences between database query tools and DM. Possible DM methodologies to be covered in the course include: multiple linear regression, clustering, k-nearest neighbor, decision trees, and multidimensional scaling. These methodologies will be augmented with real world examples from different domains such as marketing, e-commerce, and information systems. If time permits, additional topics may include privacy and security issues in data mining. The emphasis of this course is on methodologies and applications, not on their mathematical foundations.

IT 223 (or MAT 137 or MAT 242 or MAT 341 or MAT 353) is a prerequisite for this class.